1. Field of the Invention
The present invention relates broadly to the processing of information obtained by an acoustic borehole tool. More particularly, the invention relates to the real-time or post-processing of acoustic wave data to determine the formation velocity and dispersion properties of an acoustic wave propagating along the borehole using a coherence method of acoustic wave data analysis.
2. Description of the Related Art
Acoustic well logging is a well developed art, and details of acoustic logging tools and techniques are set forth in A. Kurkjian, et al., “Slowness Estimation from Sonic Logging Waveforms”, Geoexploration, Vol. 277, pp. 215–256 (1991); C. F. Morris et al., “A New Sonic Array Tool for Full Waveform Logging,” SPE-13285, Society of Petroleum Engineers (1984); A. R. Harrison et al., “Acquisition and Analysis of Sonic Waveforms From a Borehole Monopole Marzetta, “Semblance Processing of Borehole Acoustic Array Data”, Geophysics, Vol. 49, pp. 274–281 (March 1984), all of which are hereby incorporated by reference herein. An acoustic logging tool typically includes an acoustic source (transmitter), and a set of receivers that are spaced several inches or feet apart. An acoustic signal is transmitted by the acoustic source and received at the receivers of the borehole tool which are spaced apart from the acoustic source. Measurements are repeated every few inches as the tool is drawn up (or down) the borehole. The acoustic signal from source travels through the formation adjacent the borehole to the receiver array, and the arrival times and perhaps other characteristics of the receiver responses are recorded. Typically, compressional wave (P-wave), shear wave (S-wave), and Stoneley wave arrivals and waveforms are detected by the receivers and are processed. The processing of the data is often accomplished uphole or may be processed real time in the tool itself. Regardless, the information that is recorded is typically used to find formation characteristics such as formation slowness (the inverse of acoustic speed), from which pore pressure, porosity, and other formation property determinations can be made. In some tools, the acoustic signals may even be used to image the formation.
Many different techniques are known in the art for processing the acoustic wave signals in order to obtain information regarding the borehole and/or formation. Typically, the processing involves digitizing the received signal at a desired sampling rate and then processing the digitized samples according to desired techniques. Examples may be found in the references cited above, as well as in articles such as A. R. Harrison et al., “Acquisition and Analysis of Sonic Waveforms From a Borehole Monopole and Dipole Source . . . ”SPE 20557, pp. 267–282 (September 1990).
Compressional slowness has been computed using Slowness-Time Coherence (STC) processing. C. V. Kimball and T. L. Marzetta, “Semblance Processing of Borehole Acoustic Array Data”, Geophysics, Vol. 49, pp. 274–281 (March 1984). In STC processing, the measured signal is time window “filtered” and stacked, and a semblance function is computed. The semblance function relates the presence or absence of an arrival with a particular assumed slowness and particular assumed arrival time. If the assumed slowness and arrival time do not coincide with that of the measured arrival, the semblance takes on a smaller value. Consequently, arrivals in the received waveforms manifest themselves as local peaks in a plot of semblance versus slowness and arrival time. These peaks are typically found in a peak-finding routine discussed in the aforementioned article by Kimball and Marzetta, which is hereby incorporated herein by reference.
Acoustic LWD has many potential applications in oil field services including seismic correlation while drilling, pore pressure and porosity determinations, and mechanical property determinations. Because telemetry cables may not be available in these situations, the transfer of data may be accomplished via the use of pulses in the flow of the drilling mud (i.e., mud pulse telemetry). While the drilling penetration rate is very slow relative to normal logging rates, data acquisition still can far exceed the highest data transmission rates in the mud. Thus, in any proposed acoustic LWD art, processing of data downhole may be highly desirable, although the downhole computing power may be limited. Alternatively, data may be stored in the memory of the downhole tool, but this could require frequent “tripping” of the drill string.
One technique that permits the downhole processing of data with limited computing power is to calculate the semblance function using time windowing and stacking of the measured acoustic signal. However, windowing the signal may result in inaccuracies and nonlinearities based on the window width for the resulting semblance. Extrapolating from the windowed semblance often results in adding new errors and amplifying existing errors.
It would be advantageous if a non-windowed technique could be used to calculate semblance and determine acoustic speed including the formation velocity. It would also be advantageous if these parameters could be calculated using each data point collected, require a minimal amount of processing, and reduce the errors typically occurring in windowed calculations of formation velocity and semblance.